Download Use of Myocardial Perfusion SPECT for Preoperative Risk

Annals of Nuclear Cardiology Vol. 1
No. 1
43-52
REVIEW ARTICLE
Use of Myocardial Perfusion SPECT for Preoperative Risk
Stratification of Non- Cardiac Surgery
Jun Hashimoto, MD, Toshiki Kazama, MD, Yoshimi Nagata, MD, Yutaka Imai, MD
Received: May 20, 2015/Revised manuscript received: June 28, 2015/Accepted: June 29, 2015
© The Japanese Society of Nuclear Cardiology 2015
Abstract
It is difficult to assess the likelihood of perioperative cardiac events mainly because of complicated
interrelationships between clinical risk and type of surgery. To overcome this problem, The American
College of Cardiology/American Heart Association（ACC/AHA）Task Force published guidelines for
perioperative cardiovascular evaluation for non-cardiac surgery. The guidelines offer the strategy of
preoperative cardiac therapy, operative performance and perioperative management depending on the
urgency of surgery, the patient$
s risk factors, findings of cardiac testing and specific surgical
considerations. Non-invasive cardiac testing including myocardial perfusion single-photon emission
computed tomography（SPECT）is recommended to be used mainly in patients with poor functional
capacity, when the results will affect patient treatment and outcomes. In the current review, we
summarized the use of stress myocardial perfusion SPECT referring to previous reports and our data,
and provided the tips for indication of SPECT in preoperative risk stratification in non-cardiac
surgery.
Keywords: Myocardial perfusion SPECT, Perioperative cardiac event, Preioperative risk stratification
Ann Nucl Cardiol 2015；1（1）
：43-52
ardiac events are important causes of perioperative
C mortality and morbidity in non-cardiac surgery.
tive therapy, operative performance and perioperative
Thus, cardiac risk should be stratified in individual
cardiac testing including myocardial perfusion imaging
patients who are to undergo surgery, but it is difficult to
to be used mainly in patients with poor functional
assess the likelihood of perioperative cardiac events
capacity（＜4 METs）
.
management. The guidelines recommend non-invasive
mainly because of complicated interrelationships be-
In the current review, we summarized the use of
tween clinical risk and type of surgery. To overcome
stress myocardial perfusion single-photon emission
this problem, The American College of Cardiology/
computed tomography（SPECT）referring to previous
American Heart Association（ACC/AHA）Task Force
reports and our data, and provided the tips for indication
published guidelines for perioperative cardiovascular
of SPECT in preoperative risk stratification in non-car-
evaluation for non-cardiac surgery（1-4）
. These guide-
diac surgery.
lines divide clinical risk factors into major, intermediate
and minor categories, and surgical procedures into high,
Preoperative risk stratification in view of cardiac
intermediate and low-risk types. These are then used to
testing
determine further preoperative examinations, preopera-
doi：10.17996/ANC. 01.01.43
Jun Hashimoto, Toshiki Kazama, Yoshimi Nagata, Yutaka Imai
Department of Radiology, Tokai University School of Medicine,
Shimokasuya 143, Isehara, Kanagawa, Japan 259-1193
E-mail: [email protected]
As mentioned above, preoperative risk stratification is
― 44 ―
Hashimoto et al.
Preoperative Risk Stratification
Ann Nucl Cardiol 2015；1（1）
：43-52
generally difficult mainly due to complicated interrela-
SPECT in preoperative risk stratification
tionships between clinical risk factors and type of
Position of SPECT in risk stratification
surgery. Preoperative stress myocardial perfusion
Fig. 1 shows the stepwise cardiac evaluation and care
imaging provides excellent negative predictive values in
program for non-cardiac surgery appeared in the
forecasting perioperative cardiac events（5）
. We re-
ACC/AHA Guidelines（3）
. Except for the emergent
ported that normal perfusion and wall motion ensure a
surgery, patients with active cardiac conditions includ-
very low likelihood of perioperative cardiac events in
ing unstable coronary disease, decompensated heart
intermediate and low-risk surgery（6）
. Accurate identi-
failure, significant arrhythmia or severe valvular heart
fication of low risk patients facilitates reductions in cost
disease, are recommended to undergo further cardiac
and preoperative waiting time because low risk
evaluation and/or treatment. When low-risk surgery is
individuals can be exempted from further cardiac
performed on a patient without active cardiac condi-
testing, including catheterization, and proceed directly
tions, incremental cardiac risk in undergoing surgery is
to surgery.
thought to be negligible. The patient who have a
On the other hand, not only SPECT but also other
functional capacity 4 METs or more can also proceed to
modalities yield insufficient positive predictive values
the planned surgery. Preoperative cardiac evaluation of
mainly because of the relatively low frequency of
patients other than the above is performed by consider-
perioperative cardiac events（7）
. In addition, periopera-
ing the number of clinical risk factors, type of surgery
tive mortality and morbidity are related to management
and results of cardiac testing. Preoperative SPECT is
of patients. Surgeons and anesthesiologists are not
also considered to be used in this step.
blinded to the results of preoperative cardiac testing.
This availability of results has an influence on decisions
Exercise or adenosine for stress testing
regarding perioperative management of patients, which
Exercise or pharmacological（adenosine）stress is
could lower the cardiac event rate and underestimate
used for myocardial perfusion SPECT to assess stress-
the predictive accuracy of preoperative examinations
induced ischemia. Exercise has advantages that stress is
including SPECT.
physiological and that exercise capacity can be an index
Since it is generally difficult to perform a prospective
associated with cardiac morbidity and mortality. In
clinical trial for assessing the predictive value on
addition, exercise myocardial SPECT allows information
patients undergoing surgery especially when the test
whether ischemia occurs within the patientI
s work
results are blinded, most studies of this kind is
capacity or not. On the other hand, pharmacological
retrospective. In such studies, authors analyzed the data
stress has an advantage that ischemia can be induced
obtained from patients who underwent preoperative
even if the patientI
s functional capacity is low. Since
SPECT. Most of them were referred for SPECT because
perioperative cardiac stress is not dependent on the
of concern about perioperative cardiac risk. Thus, these
patientI
s activities of daily living, pharmacological stress
patients do not epitomize the general population of non-
is favorable especially in patients with insufficient
cardiac surgery candidates in terms of the likelihood of
functional capacity.
cardiac events. This increases the rate of perioperative
cardiac events.
SPECT indices for risk stratification
Furthermore, the effect of preoperative revasculariza-
Electrocardiogram（ECG）
-gated stress myocardial
tion remains unclear. There are some papers showing
perfusion SPECT yields information on myocardial
that preoperative revascularization is ineffective to
perfusion, cardiac function and left ventricular volumes.
reduce the cardiac event rate（8,9）
. However, the
It offers various indices including the summed stress
effect of preoperative revascularization depends on the
score（SSS）,summed rest score（SRS）,summed differ-
selection of patients undergoing revascularization.
ence score（SDS）,ejection fraction（EF）,end-diastolic
Further studies are required to clarify the usefulness of
volume（EDV）
, end-systolic volume（ESV）,and so on.
SPECT in identifying patients who receive prognostic
SRS and SDS reflect the size of myocardial scar and the
benefit from preoperative revascularization.
amount of stress-induced ischemia, respectively. It has
It is generally difficult to elucidate the cost-effective-
been reported that SRS, SDS and SSS are associated
ness of perioperative SPECT, because of relatively low
with perioperative cardiac events（6,10-13）.The SSS is
frequency of perioperative cardiac events, high cost of
thought to have a considerable prognostic value because
examination and uncertainty of the effect of preopera-
it reflects both scar and ischemia（6, 13）
.
tive revascularization as mentioned above.
Differences between rest and stress functional variables
Hashimoto et al.
Preoperative Risk Stratification
Ann Nucl Cardiol 2015；1（1）
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Table 1
Clinical Risk Factors and Surgical Risk
Grade
Clinical risk
Contents
Major
Unstable coronary syndromes; Decompensated heart failure; Significant arrythmias; Severe
valvular disease
Intermediate
Mild angina pectoris; Prior myocardial infarction; Compensated or prior heart failure;
Diabetes Mellitus; Renal insufficiency
Advanced age; Abnormal ECG; Rhythm other than sinus; Low functional capacity; History of
stroke; Hypertension
Emergent major operations; Aortic and other major vascular surgery; Peripheral vascular
surgery; Anticipated prolonged surgical procedures associated with large fluid shift and/or
blood loss
Carotid endarterectomy; Head and neck; Intraperitoneal and intrathoracic; Orthopedic;
Prostate
Endoscopic procedures; Superficial procedures; Cataract; Breast
（cited from reference No. 2）
Minor
Surgical risk
― 45 ―
High
Intermediate
Low
are markers of stress-induced ischemia（14-16）.However,
disease, heart failure, or cerebrovascular disease, as the
it is reported that a post-stress depression of EF was
intermediate risk factors. It is pointed out that 4 to 6
not associated with perioperative cardiac events（6）
.
weeks are reasonable to wait to perform elective
This is attributable to the use of pharmacological stress
surgery after myocardial infarction, if a recent stress
instead of exercise, and to the cohort undergoing
test does not indicate residual myocardium at risk.
preoperative SPECT. Exercise increases myocardial
The minor category comprises advanced age（grea-
oxygen consumption and facilitates the likelihood of
ter than 70 years）, abnormal ECG（LV hypertrophy,
post-ischemic stunning. On the other hand, pharmacolo-
left bundle-branch block, ST-T abnormalities）
, rhythm
gical stress causes ischemia through coronary steal that
other than sinus, and uncontrolled systemic hyperten-
develops mainly in patients with severe coronary
sion. Although these are not proven to increase
stenosis. Since preoperative SPECT is usually per-
perioperative risk independently, the presence of
formed as a screening procedure, only a limited part of
multiple minor predictors might lead to a higher
the patients have severe coronary artery disease
suspicion of coronary artery disease. These are not
（CAD）
. Therefore, the EF depression after adenosine
incorporated into the recommendations for treatment in
infusion is thought to have limited prognostic value for
the guidelines.
this cohort.
Risk of surgical procedures
Clinical risk factors
As indicated in Table 1, the ACC/AHA guidelines
Many investigators have identified preoperative
divide surgical procedures into high, intermediate and
clinical markers related to postoperative cardiac events,
low-risk types（3）. The high-risk group mainly con-
the most frequent being advanced age, hypertension,
sists of vascular surgery, and the low-risk type
diabetes, angina pectoris, arrhythmias, history of
comprises superficial or minimally invasive procedures
myocardial infarction, heart failure, prior coronary
including endoscopic surgery. The remaining general
artery bypass grafting（CABG）and abnormality in
surgery is classified into the intermediate-risk group.
electrocardiography（10,11,17-20）.As shown in Table 1,
Perioperative cardiac event rates expected are ＞5%, 1
the ACC/AHA guidelines divide clinical risk factors into
to 5%, and ＜1%, corresponding to the high, intermediate
major, intermediate and minor categories（3）
.
and low-risk surgery.
The major category includes unstable coronary
disease,
decompensated
heart
failure,
Although there have been enough data concerning
significant
the use of SPECT for preoperative risk stratification in
arrhythmia and severe valvular heart disease listed as
high and intermediate-risk surgery（3-24）
, little are
active cardiac conditions in Fig. 1. The presence of 1 or
available about low-risk surgery（6,12,13）, despite
more of these conditions mandates intensive manage-
recent widespread acceptance of minimally invasive
ment and may result in delay or cancellation of surgery
surgical techniques including endoscopy. Accumulating
unless the surgery is emergent.
prognostic data about operations associated with
The guidelines selected diabetes mellitus（DM）
,
renal insufficiency, and the history of ischemic heart
different levels of risk is useful especially when changing
a surgical approach to minimally invasive one for
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Hashimoto et al.
Preoperative Risk Stratification
Ann Nucl Cardiol 2015；1（1）
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Fig. 1 Stepwise approach to preoperative cardiac assessment
＊
: unstable coronary disease, decompensated heart failure, significant arrhythmia and severe
valvular heart disease, ＊＊: indicated in Table 1, ＊＊＊: diabetes mellitus, renal insufficiency, and the
history of ischemic heart disease, heart failure, or cerebrovascular disease.（cited from reference
No. 3）
patients with a high estimated cardiac risk, because
neural network generally allows lower computational
such data show that cardiac risk is reduced by such
burden and is reported to be more accurate in
choices. We showed that gated myocardial perfusion
predicting cardiac events for high-risk patients com-
SPECT has an incremental prognostic value in in-
pared with a logistic regression model（21）
.
termediate, but not in low-risk, non-cardiac surgery as
indicated in Fig. 2（6）
.
We generated linear and support vector machine
（SVM）classifiers, and evaluated their accuracies in
predicting perioperative cardiac events in all types of
Integrating information in preoperative risk strati-
non-cardiac surgery including high, intermediate and
fication
low-risk procedures（13）
. In addition, we estimated an
Before surgery, we can obtain various kinds of
incremental prognostic value of SPECT indices in each
information, including clinical and surgical risk, and
model. The SVM is a kind of supervised learning
indices obtained from various preoperative examina-
methodology that yields an appropriate discrimination
tions as mentioned above. Consequently, it is important
program by using data whose inputs and accurate
to seek methods to integrate the above information in
outputs are already known（training dataset）. It first
risk stratification.
generates an N-dimensional hyperplane that best
Some investigators used mathematical models to
separates the training data into two different half
provide the likelihood of perioperative cardiac events on
spaces, and then classify unknown de novo data by
the basis of clinical risk and SPECT findings（19,21）
.
determining the half space they belong to. We intro-
They employed a Bayesian model or an artificial neural
duced a SVM in preoperative risk stratification. In this
network as a tool to calculate the expected cardiac event
context, the above two half spaces equal to the two
rates. Advantages of the Bayesian model are that it
situations: the presence and absence of cardiac events,
permits consideration of the procedure-specific institu-
and the training dataset consists of data of each patient
tional complication rate in the estimation of risk and that
whose predictive variables and the prognostic outcome
it is not necessary to assume independence between
are already known. The hyperplane is determined by a
variables included in the model（19）
. The artificial
cluster of data located near the border of the two spaces,
Hashimoto et al.
Preoperative Risk Stratification
Ann Nucl Cardiol 2015；1（1）
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― 47 ―
Fig. 2 Incremental value of information about myocardial perfusion or cardiac function in predicting all cardiac events
Stratification with summed rest score（A）,summed stress score（B）,LVEF at rest（C）,and LVEF after stress（D）.
In each panel, patients were divided into 4 subgroups with clinical risk factors and operation risk. In each subgroup,
patients were sorted again into three groups（closed, hatched and unfilled bars）according to the following threshold
values of SPECT indices.
closed bar,（A）summed rest score＞7,（B）summed stress score＞9,（C）and（D）LVEF＜45%; hatched bar,（A）
1＜summed rest score＜6,（B）1＜summed stress score＜8,（C）and（D）46%＜LVEF＜59%; unfilled bar,（A）
summed rest score＝0,（B）summed stress score＝0,（C）and（D）LVEF＞60%; ＊. p＜0.05; ＊＊, p＜0.01（comparison
between the unfilled bar and others）.
The total numbers of patients are 1220 in（A）and（B）, and 868 in（C）and（D）. The threshold values（summed
stress score＝9. summed rest score＝7, and LVEF＝45%）were determined on the basis of the mean and standard
deviation: approximately mean＋s.d. in perfusion scores, and mean−s.d. in LVEF.（cited from reference No. 6）
which are called support vectors. The SVM analysis
was reduced by introducing SPECT indices（without
selects the appropriate hyperplane to maximize the
SPECT: 34.9%, with SPECT: 22.1%）
, which means that
margin between the hyperplane and support vectors.
the analysis became stable.
Among supervised learning methodologies, SVM is
thought to be one of the most accurate techniques.
This study included 1351 consecutive patients who
Perioperative risk in specific group of patients
Clinical markers related to cardiac events
were referred for preoperative dipyridamole stress
As mentioned above, various factors have been
myocardial perfusion scintigraphy and underwent non-
identified as preoperative clinical markers related to
cardiac surgery. Predictors（the input candidates for
postoperative cardiac events, including advanced age,
the classifiers）comprise one operation risk, 13 clinical
hypertension, diabetes, angina pectoris, arrhythmias,
risk, 3 SPECT perfusion indices, and 3 SPECT functional
history of myocardial infarction, congestive heart failure,
indices. The results are indicated in Tables 2 and 3. In
prior CABG and abnormal baseline electrocardiography
predicting all cardiac events, the SVM models yielded
（10,11,17-20）. In this review, we focused on aging,
favorable predictive performance compared with the
diabetes and ECG abnormality as clinical risk factors
linear models regardless of the use of SPECT results
related to perioperative cardiac events.
（Table 2）
. The incremental prognostic value of SPECT
was considerable in the linear model. In predicting hard
events（Table 3）
, the percentage of the support vector
Aging
Recently, the number of the aged undergoing surgical
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Hashimoto et al.
Preoperative Risk Stratification
Table 2
Classifier
SVM
Ann Nucl Cardiol 2015；1（1）
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Predicting All Cardiac Events
Input variables
Sensitivity（%）
Specificity（%）
AUC
Clinical＋SPECT
97.4
72.2
0.884
Clinical only
85.5
76.5
0.861
Linear
Clinical＋SPECT
67.1
75.4
0.748
Clinical only
72.4
62.4
0.677
AUC: area under the ROC curve, SVM: support vector machine-based classifier, Linear: linear
classifier（cited from reference No. 13）
Table 3
Predicting Hard Events
Classifier
SVM
Input variables
Sensitivity（%）
Specificity（%）
AUC
Clinical＋SPECT
92.9
86.2
0.892
Clinical only
85.7
76.7
0.867
Linear
Clinical＋SPECT
85.7
81.5
0.864
Clinical only
71.4
79.4
0.768
AUC: area under the ROC curve, SVM: support vector machine-based classifier, Linear: linear
classifier（cited from reference No. 13）
Preoperative diagnosis of ischemic heart disease is
difficult in the elderly because of reduced physical
activity resulting in the reduction of demand angina and
suboptimal performance in exercise cardiac testing. In
such patients, a pharmacological stress test incorporating myocardial perfusion SPECT or echocardiogram is
often of greater diagnostic or prognostic accuracy
（24-26）. A number of investigators have pointed out
that aging increases the likelihood of perioperative
cardiac events in non-cardiac surgery, and that age is an
independent predictor of perioperative events（10,17,
Fig. 3 Influence of aging on perioperative cardiac risk
Closed bar: aged 75 or more, unfilled bar: others, High:
high-risk surgery, Intermediate: intermediate-risk surgery.
In patients with abnormal SPECT, aging had an influence
on perioperative cardiac risk.（cited from reference No. 11）
27,28）. On the other hand, advanced age is listed as a
minor clinical predictor in the ACC/AHA Guidelines
（1-3）.In these guidelines, minor predictors are defined
as markers for cardiovascular disease that have not
been proven to independently increase perioperative
risk. In addition, some authors reported that advanced
treatment increases corresponding with the extension of
age is not an independent predictor of perioperative
the lifespan. The frequency of epicardial coronary artery
outcome（29,30）.
stenosis increases with advancing age. Cardiac risk
Furthermore, it remains unclear whether the cause of
factors, which are more often present in the elderly than
increased perioperative cardiac risk is attributable to
the younger population, are thought to facilitate the
aging itself or to the associated cardiac risk factors and
progression of epicardial coronary artery stenosis and to
coronary disease. In our previous report（11）, we
affect the coronary microcirculatory function（22）
.
divided patients into different groups according to the
Besides these vascular conditions, age-related cardiac
age and SPECT findings to separate the influence of
changes include decrease in contractility, increase in
aging from that of associated coronary artery disease.
stiffness and ventricular filling pressures, decrease in
As indicated in Fig. 3, aging itself had no appreciable
beta-adrenoceptor and beta-adrenoceptor-mediated
influence on perioperative cardiac risk in patients with
modulation of inotropy and chronotropy, increase in left
normal myocardial perfusion. In contrast, in patients
atrial pressure/size and action potential time, and
with perfusion abnormality, cardiac event rate increases
decrease in coronary flow reserve（23）
. All of the above
following aging, independently of other clinical variables.
changes are possible candidates for explaining increased
DM
perioperative cardiac risk in the elderly.
The prevalence of CAD is reported to be high in
Ann Nucl Cardiol 2015；1（1）
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Hashimoto et al.
Preoperative Risk Stratification
― 49 ―
Fig. 4 Surgical risk and event rate in diabetic patients
High, Intermediate and Low denote high, intermediate and
low-risk surgery, respectively.
The event rate increased depending on surgical risk when
patients manifested abnormal perfusion findings, while such
tendency was not observed in patients with normal
perfusion.（cited from reference No. 12）
Fig. 5 Risk stratification by combining information about
myocardial perfusion and cardiac function in diabetic
patients
Abnormal means the presence of abnormality in perfusion
and/or wall motion.
Combining information about myocardial perfusion and
wall motion improved predictive value of cardiac events
（cited from reference No. 12）
diabetic patients（31-33）
. The AHA pointed out that
kinds of surgery will augment cardiac risk in asymp-
patients with DM belong to the same high-risk category
tomatic DM patients. As indicated in Fig. 4, the cardiac
as patients with known CAD（34）
. Furthermore, it is
event did not occur when patients underwent low-risk
reported that cardiac death is the prominent cause for
surgery regardless of perfusion findings, indicating the
the mortality in type II DM patients（35,36）
.
limited value of SPECT before low-risk surgery.
Diabetic patients also have higher postoperative
However, the DM patients undergoing high-risk
cardiac mortality and morbidity rates than those
operation should be of particular concern if they have
without DM（37）
. The leading causes of death in DM
abnormal SPECT findings.
patients undergoing non-cardiac surgery are related to
cardiac complications（38）
. However, up to 65% of
ECG abnormality
myocardial ischemia or infarction is clinically silent
Stress ECG is often used for selecting patients with a
（39-41）
. It is important and difficult to stratify
high probability of perioperative cardiac events because
perioperative cardiac risk of DM patients because of the
of its availability and low cost. The onset of a myocardial
high prevalence of asymptomatic myocardial ischemia
ischemic response at low exercise workload is associated
or infarction that is not so easy to diagnose. Moreover, it
with increased risk of perioperative cardiac events
is reported that that clinical risk factors are not of
（2,3）.However, the usefulness of ECG for preoperative
prognostic value in asymptomatic DM patients in
risk assessment is still controversial. A prospective
predicting perioperative cardiac events（42）
.
study showed that ST segment depression in exercise
Myocardial SPECT is reported to have a prognostic
ECG is an independent predictor of perioperative
value in DM patients with cardiac disease undergoing
cardiac complications（44）
. On the other hand, some
non-cardiac surgery（43）
. However, it remains unclear
papers clarified the superiority of myocardial perfusion
whether SPECT is of prognostic value in DM patients
imaging and limitation of exercise ECG in preoperative
without overt cardiac symptoms. We investigated the
risk stratification（45,46）.Duke treadmill score（DTS）
usefulness of clinical risk factors, DM indexes and ECG-
is widely used for risk stratification in patients
gated SPECT findings in stratifying perioperative
undergoing treadmill test. It is reported that one third of
cardiac risk（12）
. The duration was the only DM index
patients with high-risk DTS manifested normal SPECT
of prognostic value. Normal myocardial SPECT findings
findings and that such patients are associated with low
ensure the low likelihood of perioperative cardiac events
risk of cardiac events（47）
. However, it is not easy to
in DM patients without chest pain（Fig. 4）
. Simul-
routinely conduct stress myocardial SPECT within
taneous assessment of myocardial perfusion and cardiac
limited time before surgery and the problem of the
function by using ECG-gated SPECT was proved to
examination cost also exists. Although the ACC/AHA
yield more accurate risk stratification（Fig. 5）
.
Guidelines recommend myocardial perfusion study in
In clinical practice, it is also worthy investigating what
patients with high cardiac risk estimated by stress ECG
― 50 ―
Hashimoto et al.
Preoperative Risk Stratification
Ann Nucl Cardiol 2015；1（1）
：43-52
Sources of Funding
This research was partially supported by Grant-inAid Scientific Research（18790912）from the Ministry
of Education, Culture, Sports, Science and Technology.
Conflicts of Interest
None
Reprint requsts and correspondence：
Jun Hashimoto,
Department of Radiology, Tokai University School of
Fig. 6 Risk stratification by combining information about
myocardial perfusion and cardiac function in patients with
positive findings in stress ECG
Classification 1: combination of summed stress score and
stress LVEF; Classification 2: combination of summed stress
score and stress LVEDV.
The numbers in parentheses are the number of patients
with cardiac events/total number in the category.
if it will change management, there seems to be limited
number of reports about preoperative risk stratification
with myocardial SPECT after sorting the patients with
stress ECG（48）
.
We collected data of patients with positive findings in
preoperative stress ECG from our SPECT database to
clarify whether myocardial perfusion SPECT stratifies
risk of perioperative cardiac events. We also assessed
prognostic value of combining perfusion and functional
data obtained with ECG gated SPECT. Combination of
information about myocardial perfusion and cardiac
function was successful in separating patients of high
risk causing 55% of all cardiac events from others of low
risk including more than 80% of all the patients（Fig. 6）
.
Conclusions
In non-cardiac surgery, preoperative therapy, operative performance and perioperative management are
determined by considering the urgency of surgery,
patientI
s risk factors, specific surgical risk and findings
of cardiac testing including SPECT. Although myocardial perfusion SPECT has been used for risk stratification mainly in high-risk surgery, some investigators
pointed out its prognostic value in intermediate-risk
surgery. It is important to seek methods to evaluate
perioperative risk by integrating information of clinical
and surgical risk, and SPECT findings.
Acknowledgments
None
Medicine, Shimokasuya 143, Isehara, Kanagawa,
Japan 259-1193
E-mail：[email protected]
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